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纵向研究中删失分位数回归模型的推断AI 解读

We develop inference procedures for longitudinal data where some of the measurements are censored by fixed constants. We consider a semi-parametric quantile regression model that makes no distributional assumptions. Our research is motivated by the lack of proper inference procedures for data from biomedical studies where measurements are censored due to a fixed quantification limit. In such studies the focus is often on testing hypotheses about treatment equality. To this…

均匀分布尺度同质性的双侧与单侧检验AI 解读

Consider the model where Xij, i = 1, 2, …, k; j = 1, …, n i are independent uniform random variables with scale parameter θ i > 0. Test H 0: θl = ··· = θ k versus H 2: not H 0. Also consider the alternative H 1: θl ≤ ··· ≤ θ k . For H 0 versus H 2 and n i = n, we obtain a complete class of constant-size permutation invariant tests and show that each test in the class is unbiased. The likelihood ratio test and others are in this class. For H 0 versus H 1 we obtain a complete…

均匀分布尺度同质性检验：双侧与有序单侧备择AI 解读

Consider the model where Xij, i = 1, 2, …, k; j = 1, …, n i are independent uniform random variables with scale parameter θ i > 0. Test H 0: θl = ··· = θ k versus H 2: not H 0. Also consider the alternative H 1: θl ≤ ··· ≤ θ k . For H 0 versus H 2 and n i = n, we obtain a complete class of constant-size permutation invariant tests and show that each test in the class is unbiased. The likelihood ratio test and others are in this class. For H 0 versus H 1 we obtain a complete…

右删失线性回归分析中的分层使用AI 解读

We study two modified synthetic data least-squares estimation methods for linear regression models with right censored response variables, unspecified residual distributions and random censoring variables which may not be i.i.d. These methods are the result of an investigation into the use of stratification. We conclude that stratification should be used whether or not the censoring variables are dependent on the covariates. We give the asymptotic results of the estimators…

删失数据的单调估计方程AI 解读

The monotone class rank-test-based estimating equations for regression models with right censored data is considered. We introduce an estimator which is a solution of a monotone estimating equation that is an extension of the Gehan test. The estimator is easy to derive, $\sqrt n$-consistent and asymptotically normal under minimal conditions. All monotone estimating equations are characterized, and a simulation study, which shows that our suggested procedure performs well, is…